초록

Dynamic Source Routing protocol is one of the most promising among on demand category of protocols for MANETs. Demands of network performance conflict with the demands of mobile networks . To enhance the QoS in a protocol like DSR we used ANN which helps to preserve the resources of the MANET leading to improvement in performance of DSR. While routing the data, If a legitimate node is mistaken as rogue node then also the QoS suffers and if a rogue node is not detected then also it can consume the resources of the network and deteriorate the QoS . In this work a neural network has been further optimized to improve its accuracy by varying the number of layers in it. A typical wireless network scenario of DSR has been simulated in NS2 and then a rogue node has been introduced to mimic attack. The parameters from the trace files have been used to train a neural network simulated in Matlab and its effectiveness has been improved to make the detection of intrusion more accurate. Although previous work has been reported in the area of application of neural networks for intrusion detection but there is a scope of improvement in this technique by varying the number of layers of ANN, making it more effective and improving the QoS of MANET.